Founding Infrastructure Engineer

Posted Yesterday
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Santa Clara, CA, USA
Hybrid
200K-240K Annually
Senior level
Artificial Intelligence • Computer Vision • Machine Learning • Software
The Role
Build and scale the infrastructure layer for Vision-Language Models: own VLM inference stack (GPU serving, latency/cost), design multimodal developer APIs, ensure reliability and observability, implement backend systems and scalable data pipelines, and drive production-grade developer experience and testing discipline.
Summary Generated by Built In

Join us as we build VLM Run – the enterprise infrastructure layer for visual intelligence. Our mission is to give developers a unified way to fine-tune, specialize, and run Vision-Language Models (VLMs) that turn images, PDFs, screenshots, and video into reliable, schema-true structured data for production insights and automation – built for scale, security, and SLAs.

We’re looking for senior or staff-level engineers to help us build and scale the infrastructure layer for visual intelligence. You’ll do well here if you bring strong technical craft, high ownership, and strength in one or more of these areas:

  • Platform & Infra: Own and optimize the VLM inference stack (see Orion) end-to-end – from GPU serving and latency/cost to scalable backend systems and reliability.

  • Developer Experience: Design clean, ergonomic APIs for multimodal apps – tool/function calling, structured outputs, and workflows developers actually want to build.

  • High Agency + Velocity: We move fast on hard problems. You’ll take ideas from 0→1, set the bar for quality, and help define what “production-grade visual intelligence” looks like.

🎓 Required Expertise (5+ YoE - Senior or Staff-level)

  • LLM/VLM Experience: Integrated or built applications with LLMs or VLMs (OpenAI, HuggingFace, Ollama, vLLM), with an understanding of prompt engineering, function calling, and structured outputs.

  • Backend Engineering: Python, FastAPI, async API design, schema validation, caching, and performance optimization.

  • Infra & DevOps: Docker, Kubernetes, CI/CD, observability (logging, metrics, tracing), GCP or AWS.

  • Datastores & Systems: Postgres, MongoDB, Redis; experience with scalable, reliable data pipelines.

  • Developer Experience: Strong testing discipline (TDD), clean code, GitHub workflows (PRs, reviews, CI), and internal tooling mindset.

  • [BONUS] SaaS Experience: Shipped full-stack dev platforms or SaaS products – from landing pages to auth, billing, telemetry, and infra. Email us with a one-liner if you've done this.

🗒️ Other Details

  • Pay + Equity Range: $200K-$240K / yr, 1-3% equity

  • Competitive compensation and benefits: We pay market rate for seed-stage startups + equity options, offer great healthcare and 401K.

  • In-person: At least 4 days a week in Santa Clara, CA (we’re right by 101, next to AMD’s HQ offices).

Skills Required

  • 5+ years experience; Senior or Staff-level engineer
  • Experience integrating or building applications with LLMs/VLMs (OpenAI, HuggingFace, Ollama, vLLM); prompt engineering, function calling, structured outputs
  • Backend engineering with Python, FastAPI, async API design, schema validation, caching, and performance optimization
  • Infrastructure and DevOps: Docker, Kubernetes, CI/CD, observability (logging, metrics, tracing), GCP or AWS
  • Datastores and systems experience: Postgres, MongoDB, Redis; building scalable, reliable data pipelines
  • Developer experience focus: strong testing discipline (TDD), clean code, GitHub workflows (PRs, reviews, CI), internal tooling mindset
  • High ownership and ability to take ideas from 0->1; strong technical craft and velocity
  • In-person presence at least 4 days a week in Santa Clara, CA
  • SaaS experience (shipped full-stack dev platforms or SaaS products including auth, billing, telemetry, infra)
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The Company
6 Employees
Year Founded: 2022

What We Do

VLM Run is an enterprise infrastructure platform for visual intelligence, providing a unified API to fine-tune, specialize, and operationalize Vision Language Models (VLMs). The company enables enterprises to seamlessly process and extract structured, schema-true JSON data from unstructured visual sources, including images, PDFs, and videos, designed for production-grade accuracy, security, and scalability.

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